SoroushVahidi/scidocs huggingface dataset:
Computer analysis of computed tomography scans of the lung: a survey
(2006)

Current computed tomography (CT) technology allows for near isotropic, submillimeter resolution acquisition of the complete chest in a single breath hold. These thin-slice chest scans have become indispensable in thoracic radiology, but have also substantially increased the data load for radiologists. Automating the analysis of such data is, therefore, a necessity and this has created a rapidly developing research area in medical imaging. This paper presents a review of the literature on computer analysis of the lungs in CT scans and addresses segmentation of various pulmonary structures, registration of chest scans, and applications aimed at detection, classification and quantification of chest abnormalities. In addition, research trends and challenges are identified and directions for future research are discussed.
A 0.5-V bulk-input fully differential operational transconductance amplifier
(2004)

We present a fully differential two-stage Miller op-amp operating from a 0.5 V power supply. The input signal is applied to the bulk nodes of the input devices. A prototype was designed in a standard 0.18 /spl mu/m CMOS process using standard 0.5 V V/sub T/ devices. It has a measured 52 dB DC gain, a 2.5 MHz gain-bandwidth and consumes 110 /spl mu/W.
A 40-50-GHz SiGe 1 : 8 differential power divider using shielded broadside-coupled striplines
(2008)

This paper presents a 1 : 8 differential power divider implemented in a commercial SiGe BiCMOS process using fully shielded broadside-coupled striplines integrated vertically in the silicon interconnect stackup. The 1 : 8 power divider is only 1.12 x1.5 mm2 including pads, and shows 0.4-dB rms gain imbalance and <3deg rms phase imbalance from 40 to 50 GHz over all eight channels, a measured power gain of 14.9 plusmn0.6 dB versus a passive divider at 45 GHz, and a 3-dB bandwidth from 37 to 52 GHz. A detailed characterization of the shielded broadside-coupled striplines is presented and agrees well with simulations. These compact lines can be used for a variety of applications in SiGe/CMOS millimeter-wave circuits, including differential signal distribution, miniature power dividers, matching networks, filters, couplers, and baluns.
A –$21.2$ -dBm Dual-Channel UHF Passive CMOS RFID Tag Design
(2014)

Previous research results showed that UHF passive CMOS RFID tags had difficulty to achieve sensitivity less than -20 dBm. This paper presents a dual-channel 15-bit UHF passive CMOS RFID tag prototype that can work at sensitivity lower than -20 dBm. The proposed tag chip harvests energy and backscatters uplink data at 866.4-MHz (for ETSI) or 925-MHz (for FCC) channel and receives downlink data at 433-MHz channel. Consequently, the downlink data transmission does not interrupt our tag from harvesting RF energy. To use the harvested energy efficiently, we design a tag chip that includes neither a regulator nor a VCO such that the harvested energy is completely used in receiving, processing, and backscattering data. Without a regulator, our tag uses as few active analog circuits as possible in the receiver front-end. Instead, our tag uses a novel digital circuit to decode the received data. Without a VCO, the design of our tag can extract the required clock signal from the downlink data. Measurement result shows that the sensitivity of the proposed passive tag chip can reach down to -21.2 dBm. Such result corresponds to a 19.6-m reader-to-tag distance under 36-dBm EIRP and 0.4-dBi tag antenna gain. The chip was fabricated in TSMC 0.18- μm CMOS process. The die area is 0.958 mm ×0.931mm.
Quantifying and Visualizing Attribute Interactions
(2003)

Interactions are the prototypical examples of unexpected and irreducible patterns in data that encompass several attributes. We attempt to unify the divergent definitions and conceptions of interactions present in the literature, and propose two separate conceptions of what interactions are: if a group of attributes interacts observationally, we cannot understand their relationship without looking at all the attributes simultaneously; if a group of attributes interacts representationally, we cannot create a model that would not include conditions involving all the attributes. Rather than test for interactions, we attempt to quantify them, and visually present the most important interactions of the data. Our quantification is based on how well we can approximate a joint probability distribution without admitting that there are interactions. Judging from these illustrations, most machine learning procedures are not treating interactions appropriately.
18 kW three phase inverter system using hermetically sealed SiC phase-leg power modules
(2010)

Power electronics play an important role in electricity utilization from generation to end customers. Thus, high-efficiency power electronics help to save energy and conserve energy resources. Research on silicon carbide (SiC) power electronics has shown their better efficiency compared to Si power electronics due to the significant reduction in both conduction and switching losses. Combined with their high-temperature capability, SiC power electronics are more reliable and compact. This paper focuses on the development of such a high efficiency, high temperature inverter based on SiC JFET and diode modules. It involves the work on high temperature packaging (>200 °C), inverter design and prototype development, device characterization, and inverter testing. A SiC inverter prototype with a power rating of 18 kW is developed and demonstrated. When tested at moderate load levels compared to the inverter rating, an efficiency of 98.2% is achieved by the initial prototype without optimization, which is higher than most Si inverters.
Training Deep Neural Networks on Noisy Labels with Bootstrapping
(2015)

Current state-of-the-art deep learning systems for visual object recognition and detection use purely supervised training with regularization such as dropout to avoid overfitting. The performance depends critically on the amount of labeled examples, and in current practice the labels are assumed to be unambiguous and accurate. However, this assumption often does not hold; e.g. in recognition, class labels may be missing; in detection, objects in the image may not be localized; and in general, the labeling may be subjective. In this work we propose a generic way to handle noisy and incomplete labeling by augmenting the prediction objective with a notion of consistency. We consider a prediction consistent if the same prediction is made given similar percepts, where the notion of similarity is between deep network features computed from the input data. In experiments we demonstrate that our approach yields substantial robustness to label noise on several datasets. On MNIST handwritten digits, we show that our model is robust to label corruption. On the Toronto Face Database, we show that our model handles well the case of subjective labels in emotion recognition, achieving state-of-theart results, and can also benefit from unlabeled face images with no modification to our method. On the ILSVRC2014 detection challenge data, we show that our approach extends to very deep networks, high resolution images and structured outputs, and results in improved scalable detection.
The Type of Information Overload Affects Electronic Knowledge Repository continuance
(2008)

In the present competitive organizational environment more organizations are implementing knowledge management initiatives to gain strategic advantage. One such initiative is that of implementing electronic knowledge repositories (EKR) which often leads to a rapid increase in the quantity of information employees must process daily, raising concerns of employees being overloaded. This is especially true for current EKRs using distributive technology, enabling customizable individual workspaces which can result in loose knowledge structures. This paper identifies a new type of information overload (IO), extending the concept as occurring in both knowledge seekers and contributors and uses cognitive dissonance theory to provide evidence that IO can change employees’ perception of EKR usage. This research paper provides the first empirical evidence that overload has no sufficient affect on EKR continuance intention directly, but has a significant negative affect on the two main success measures: Perceived usefulness and satisfaction of the system.
Learning to aggregate vertical results into web search results
(2011)

Aggregated search is the task of integrating results from potentially multiple specialized search services, or verticals, into the Web search results. The task requires predicting not only which verticals to present (the focus of most prior research), but also predicting where in the Web results to present them (i.e., above or below the Web results, or somewhere in between). Learning models to aggregate results from multiple verticals is associated with two major challenges. First, because verticals retrieve different types of results and address different search tasks, results from different verticals are associated with different types of predictive evidence (or features). Second, even when a feature is common across verticals, its predictiveness may be vertical-specific. Therefore, approaches to aggregating vertical results require handling an inconsistent feature representation across verticals, and, potentially, a vertical-specific relationship between features and relevance. We present 3 general approaches that address these challenges in different ways and compare their results across a set of 13 verticals and 1070 queries. We show that the best approaches are those that allow the learning algorithm to learn a vertical-specific relationship between features and relevance.
Clustering Validity Based on the Improved Hubert \Gamma Statistic and the Separation of Clusters
(2006)

The validity of clustering is one important research field in clustering analysis, and many clustering validity functions have been proposed, especially those based on the geometrical structure of data set, such as Dunn's index and Xie-Beni index. In this way, the compactness and the separation of clusters are usually taken into account. Xie-Beni index decreases with the number of partitions increasing. It is difficult to choose the optimal number of clusters when there are lots of clusters in data. In this paper, a novel clustering validity function is proposed, which is based on the improved Huber Gamma statistic combined with the separation of clusters. Unlike other clustering validity, the function has the only maximum with the clustering number increasing. The experiments indicate that the function can be used as the optimal index for the choice of the clustering numbers
A Dual-Polarized Dual-Band Antenna With High Gain for 2G/3G/LTE Indoor Communications
(2018)

A compact dual-polarized dual-band omnidirectional antenna with high gain is presented for 2G/3G/LTE communications, which comprise two horizontal polarization (HP) and a vertical polarization (VP) elements. The upper HP element consists of four pairs of modified printed magneto-electric (ME) dipoles that are fed by a four-way power divider feeding network, and eight pieces of arc-shaped parasitic patches that are printed on both sides of the circular printed circuit board alternately. The four-way power divider feeding network together with the four pairs of ME dipoles mainly provide a stable 360° radiation pattern and high gain, while the eight pieces of patches are used to enhance the bandwidth. The lower HP element is similar to the upper one except that it do not have the parasitic patches. The VP element consists of four pairs of cone-shaped patches. Different from the HP element, the upper VP element provides the lower frequency band while the lower VP one yields the upper frequency band. The VP element and the HP element are perpendicularly arranged to obtain the compact and dual-polarized features. Measured results show that a bandwidth of 39.6% (0.77–1.15 GHz) with a gain of about 2.6 dBi and another bandwidth of 55.3% (1.66–2.93 GHz) with a gain of about 4.5 dBi can be achieved for the HP direction, while a bandwidth of 128% (0.7–3.2 GHz) with a gain of around 4.4 dBi can be acquired for the VP direction. Port isolation larger than 20 dB and low-gain variation levels within 2 dBi are also obtained. Hence, the proposed antenna is suitable for 2G/3G/LTE indoor communications.
Mature HIV-1 capsid structure by cryo-electron microscopy and all-atom molecular dynamics
(2013)

Retroviral capsid proteins are conserved structurally but assemble into different morphologies. The mature human immunodeficiency virus-1 (HIV-1) capsid is best described by a ‘fullerene cone’ model, in which hexamers of the capsid protein are linked to form a hexagonal surface lattice that is closed by incorporating 12 capsid-protein pentamers. HIV-1 capsid protein contains an amino-terminal domain (NTD) comprising seven α-helices and a β-hairpin, a carboxy-terminal domain (CTD) comprising four α-helices, and a flexible linker with a 310-helix connecting the two structural domains. Structures of the capsid-protein assembly units have been determined by X-ray crystallography; however, structural information regarding the assembled capsid and the contacts between the assembly units is incomplete. Here we report the cryo-electron microscopy structure of a tubular HIV-1 capsid-protein assembly at 8 Å resolution and the three-dimensional structure of a native HIV-1 core by cryo-electron tomography. The structure of the tubular assembly shows, at the three-fold interface, a three-helix bundle with critical hydrophobic interactions. Mutagenesis studies confirm that hydrophobic residues in the centre of the three-helix bundle are crucial for capsid assembly and stability, and for viral infectivity. The cryo-electron-microscopy structures enable modelling by large-scale molecular dynamics simulation, resulting in all-atom models for the hexamer-of-hexamer and pentamer-of-hexamer elements as well as for the entire capsid. Incorporation of pentamers results in closer trimer contacts and induces acute surface curvature. The complete atomic HIV-1 capsid model provides a platform for further studies of capsid function and for targeted pharmacological intervention.
Quantitative functional evaluation of a 3D-printed silicone-embedded prosthesis for partial hand amputation: A case report.
(2017)

STUDY DESIGN
A male patient with partial hand amputation of his nondominant hand, with only stumps of the proximal phalanx of the first and fifth finger, was evaluated. The performance of using two alternative 3D printed silicone-embedded personalized prostheses was evaluated using the quantitative Jebsen Hand Function Test.


INTRODUCTION
Custom design and fabrication of 3D printed prostheses appears to be a good technique for improving the clinical treatment of patients with partial hand amputations. Despite its importance the literature shows an absence of studies reporting on quantitative functional evaluations of 3D printed hand prostheses.


PURPOSE OF THE STUDY
We aim at producing the first quantitative assessment of the impact of using 3D printed silicone-embedded prostheses that can be fabricated and customized within the clinical environment.


METHODS
Alginate molds and computed tomographic scans were taken from the patient's hand. Each candidate prosthesis was modeled in Computer Aided Design software and then fabricated using a combination of 3D printed parts and silicone-embedded components.


DISCUSSION
Incorporating the patient's feedback during the design loop was very important for obtaining a good aid on his work activities. Although the explored patient-centered design process still requires a multidisciplinary team, functional benefits are large.


CONCLUSION(S)
Quantitative data demonstrates better hand performance when using 3D printed silicone-embedded prosthesis vs not using any aid. The patient accomplished complex tasks such as driving a nail and opening plastic bags. This was impossible without the aid of produced prosthesis.
Graphical Models for Probabilistic and Causal Reasoning
(1997)

This chapter surveys the development of graphical models known as Bayesian networks, summarizes their semantical basis and assesses their properties and applications to reasoning and planning. Bayesian networks are directed acyclic graphs (DAGs) in which the nodes represent variables of interest (e.g., the temperature of a device, the gender of a patient, a feature of an object, the occurrence of an event) and the links represent causal influences among the variables. The strength of an influence is represented by conditional probabilities that are attached to each cluster of parents-child nodes in the network. Figure 1 illustrates a simple yet typical Bayesian network. It describes the causal relationships among the season of the year (X1), whether rain falls (X2) during the season, whether the sprinkler is on (X3) during that season, whether the pavement would get wet (X4), and whether the pavement would be slippery (X5). All variables in this figure are binary, taking a value of either true or false, except the root variable X1 which can take one of four values: Spring, Summer, Fall, or Winter. Here, the absence of a direct link between X1 and X5, for example, captures our understanding that the influence of seasonal variations on the slipperiness of the pavement is mediated by other conditions (e.g., the wetness of the pavement). As this example illustrates, a Bayesian network constitutes a model of the environment rather than, as in many other knowledge representation schemes (e.g., logic, rule-based systems and neural networks), a model of the reasoning process. It simulates, in fact, the causal mechanisms that operate in the environment, and thus allows the investigator to answer a variety of queries, including: associational queries, such as “Having observed A, what can we expect of B?”; abductive queries, such as “What is the most plausible explanation for a given set of observations?”; and control queries; such as “What will happen if we intervene and act on the environment?” Answers to the first type of query depend only on probabilistic
Semantic portrait color transfer with internet images
(2015)

We present a novel color transfer method for portraits by exploring their high-level semantic information. First, a database is set up which consists of a collection of portrait images download from the Internet, and each of them is manually segmented using image matting as a preprocessing step. Second, we search the database using Face++ to find the images with similar poses to a given source portrait image, and choose one satisfactory image from the results as the target. Third, we extract portrait foregrounds from both source and target images. Then, the system extracts the semantic information, such as faces, eyes, eyebrows, lips, teeth, etc., from the extracted foreground of the source using image matting algorithms. After that, we perform color transfer between corresponding parts with the same semantic information. We get the final transferred result by seamlessly compositing different parts together using alpha blending. Experimental results show that our semantics-driven approach can generate better color transfer results for portraits than previous methods and provide users a new means to retouch their portraits.
Real-Time Detection of Camera Tampering
(2006)

This paper presents a novel technique for camera tampering detection. It is implemented in real-time and was developed for use in surveillance and security applications. This method identifies camera tampering by detecting large differences between older frames of video and more recent frames. A buffer of incoming video frames is kept and three different measures of image dissimilarity are used to compare the frames. After normalization, a set of conditions is tested to decide if camera tampering has occurred. The effects of adjusting the internal parameters of the algorithm are examined. The performance of this method is shown to be extremely favorable in real-world settings.
Effect of Methanol Addition on the Resistivity and Morphology of PEDOT:PSS Layers on Top of Carbon Nanotubes for Use as Flexible Electrodes.
(2015)

UNLABELLED
Overcoating carbon nanotube (CNT) films on flexible poly(ethylene terephthalate) (PET) foils with poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (


PEDOT
PSS) layers reduces the surface roughness, which is interesting for use in organic electronics. Adding methanol to the


PEDOT
PSS aqueous solution used for spin coating of the


PEDOT
PSS layer improves the wetting behavior of the CNT/PET surface. Samples with different volume fractions of methanol (0, 33, 50, 67, and 75 vol %) are compared with respect to the transmission, horizontal, and vertical resistivity. With grazing-incidence small-angle X-ray scattering, the film morphologies are probed, which is challenging because of the substrate flexibility. At 50 vol %, methanol optimum conditions are achieved with the resistivity close to that of the bare CNT/PET substrates because of the best contact between the


PEDOT
PSS film and CNT surface. At lower methanol ratios, the


PEDOT
PSS films cannot adapt the CNT morphology, and at higher methanol ratios, they rupture into domains and no continuous


PEDOT
PSS layers are formed.
Business processes--attempts to find a definition
(2003)

Definitions of business process given in much of the literature on Business Process Management are limited in depth and their related models of business processes are correspondingly constrained. After giving a brief history of the progress of business process modeling techniques from production systems to the office environment, this paper proposes that most definitions are based on machine metaphor type explorations of a process. While these techniques are often rich and illuminating it is suggested that they are too limited to express the true nature of business processes that need to develop and adapt to today’s challenging environment.
A multi-view deep learning architecture for classification of breast microcalcifications
(2016)

In this paper we address the problem of differentiating between malignant and benign tumors based on their appearance in the CC and MLO mammography views. Classification of clustered breast microcalcifications into benign and malignant categories is an extremely challenging task for computerized algorithms and expert radiologists alike. We describe a deep-learning classification method that is based on two view-level decisions, implemented by two neural networks, followed by a single-neuron layer that combines the viewlevel decisions into a global decision that mimics the biopsy results. Our method is evaluated on a large multi-view dataset extracted from the standardized digital database for screening mammography (DDSM). Experimental results show that our network structure significantly improves on previously suggested methods.
Four-Dimensional Discrete-time Lotka-Volterra Models with an Application to Ecology
(2012)

This paper presents a study of the two-predators-two-preys discrete-time Lotka-Volterra model with selfinhibition terms for preys with direct applications to ecological problems. Parameters in the model are modified so that each of them has its own biological meaning, enabling more intuitive interpretation of biological conditions to the model . Moreover, the modified version is applicable to simulate a part of a large ecosystem, not only a closed predator-prey system with four species. An easy graphical method of analysis of the conditions on parameters ensuring long persistence under coexistence is presented. As an application, it is explained that a predator specie who feed on relatively small number of preys compared to the other predator species must be selective on the available preys in order for long persistence of the ecosystem. This may be regarded as a theoretical explanation of the existence of flush-pursuer birds, those who uses highly specialized hunting strategy and cross-adapts to the ecosystem relative to the ordinary bird species.